在智能电网背景下,基于LSA-SVM算法的电网安全风险评估模型的构建
Haojin Qi1, Wan Zhu1, Mingda Ye1
1State Grid Zhejiang Electric Power Co., Ltd. Ningbo Power Supply Company, Ningbo, 315000, China.
Scientific reports
|April 20, 2024
概括
这项研究介绍了一种新的融合算法,它结合了闪光搜索和支持向量机来实现智能电网安全. 改进的模型提高了准确性,减少了风险评估时间,确保了更安全的电力系统运行.
科学领域:
- 电气工程 电气工程
- 计算机科学 计算机科学
- 网络安全 网络安全
背景情况:
- 智能电网由于其复杂性而面临越来越多的安全威胁.
- 传统的安全措施与先进和隐藏的攻击作斗争.
- 需要更快,更准确的电力网络安全风险评估.
研究的目的:
- 开发用于电力网络安全风险评估的融合算法.
- 建立一个基于融合算法改进的风险评估模型.
- 为了提高智能电网安全中的准确性和计算速度.
主要方法:
- 将闪光搜索算法与支持向量机器合并.
- 开发一个改进的电力网络安全风险评估模型.
- 经验分析和与现有算法进行比较.
主要成果:
- 聚变算法实现了96.2%的准确率和3.8%的错误率.
- 改进后的模型达到97.8%的准确性,错误率为1.9%.
- 该模型展示了更快的计算时间 (4.4s) 和卓越的性能.
结论:
- 融合算法和改进的模型显著优于其他方法.
- 这种方法可以提升安全风险的早期检测.
- 这些发现支持电力系统的安全和连续运行.
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